Toward a more holistic approach to the study of exposures and child outcomes

Epigenomics. 2024 Mar 14;16(9):635-651. doi: 10.2217/epi-2023-0424. Online ahead of print.

Abstract

Aim: The current work was designed to demonstrate the application of the exposome framework in examining associations between exposures and children's long-term neurodevelopmental and behavioral outcomes. Methods: Longitudinal data were collected from birth through age 6 from 402 preterm infants. Three statistical methods were utilized to demonstrate the exposome framework: exposome-wide association study, cumulative exposure and machine learning models, with and without epigenetic data. Results: Each statistical approach answered a distinct research question regarding the impact of exposures on longitudinal child outcomes. Findings highlight associations between exposures, epigenetics and executive function. Conclusion: Findings demonstrate how an exposome-based approach can be utilized to understand relationships between internal (e.g., DNA methylation) and external (e.g., prenatal risk) exposures and long-term developmental outcomes in preterm children.

Keywords: epigenetics; exposome; machine learning; neurodevelopment; prematurity.